Commercial, residential, and industrial buildings are responsible for a significant portion of the world's total energy use. Heating and cooling account for most of a building's energy consumption and typically are the most expensive items with respect to building energy costs as electrical power for heating and cooling is often purchased at peak rates. While the cost of heating and cooling buildings is increasing, the thermal comfort of building occupants remains an important concern as such comfort supports occupants' productivity, health, and is related to optimal operating conditions for buildings whether they be residential, commercial, or industrial.
A network or buildings (or a building network) may include several connected or associated buildings. Typically, a network of buildings includes one or more commercial, institutional, industrial, and residential buildings which are distributed over a geographic area. This geographic area may be local and relatively small (e.g., a rural community or urban district) or global and covering any number of jurisdictions. The network of buildings may be operated by its owner or manager who may be an individual or corporation. Each building may include one or more thermal zones where thermal comfort control is required.
Typically, the energy supply to a building or network of buildings is provided by one or more utilities by way of electricity, steam, water, or any other energy carrier or a combination thereof delivered through one or more heating, ventilating, and air conditioning (“HVAC”) devices. These devices maintain required or desired thermal, air quality, and related operating conditions in each building of the network of buildings. For example, a building may use a heat supply from a centralized steam utility (e.g., district heating), an individual chiller, and an individual ventilation device to maintain the required temperature in each thermal zone of the building.
The operating conditions and related energy use in the network of buildings and in each individual building are typically managed by a building energy management system (“BEMS”). The building energy management system controls all HVAC devices in the network to keep thermal and air quality operating conditions in each individual building of the network within a desired range. The thermal parameters controlled by the building energy management system, hereinafter referred to as control parameters, include but are not limited to thermal zone temperature, relative humidity, and air quality. The reference values for the control parameters, hereinafter referred to as set points, include but are not limited to reference values for thermal zone temperature, reference values for relative humidity, and reference values for air quality. Typically, at any time of the day, an individual building may use only one set of set points. This set of set points is predefined, scheduled by the building operator through the BEMS, and executed by the building HVAC system.
Each building in the network of buildings operates its HVAC systems within its own unique as built and natural environment. The as built and natural environment includes: the building location; the orientation of building faces (e.g., walls and roofs); shading from surrounding landscape, vegetation and buildings; heat waves and wind ventilation corridors from urban street canyons; etc. Each building also has its own individual architectural design, including, the internal configuration of building space defined by building use, specifically, the number, location and configuration of thermal comfort zones within the building. Due to the external built environment and internal building space configuration, the ambient weather conditions affecting different building faces (e.g., direct sunlight, shading, wind direction, etc.) may create dramatically different thermal conditions in different thermal zones within the building leading to the need to heat one part of the building while cooling another part to meet the thermal comfort requirements of the buildings' occupants. The need to meet highly granular thermal comfort requirements in buildings to maintain thermal comfort in every thermal zone while minimizing the building's overall heating and cooling energy costs requires new approaches to building energy management.
In addition, as the number of buildings in a network of buildings and their cumulative energy use grows, the ability of a typical BEMS to optimize building energy use based on current and anticipated operating conditions in each building, to respond to limitations in energy resources and energy budgets, to reduce carbon footprints, and to participate in energy markets becomes increasing important. As mentioned above, these requirements call for a granular approach to managing thermal comfort in building thermal zones to support the productivity, health, and wellbeing of building occupants while minimizing the building's overall energy use, costs, and carbon footprint.
Several methods and systems for optimizing energy use in commercial, residential, and industrial buildings have been proposed. For example, U.S. Patent Application Publication No. 2011/0276527 by Pitcher, et al., entitled, “Balance Point Determination”, describes systems, methods and associated software for developing a non-linear model of energy usage for a building or asset based on a plurality of weather measurements indicating weather conditions of a region in which an asset is located and a plurality of energy consumption measurements indicating amounts of energy consumed by the asset.
As another example, U.S. Pat. No. 6,098,893 to Berglund, et al., entitled “Comfort Control System Incorporating Weather Forecast Data and a Method for Operating such a System”, describes a comfort control system for buildings that considers a number of building external factors in producing control instructions. The system includes structure for receiving weather forecast data, structure for combining the data with a group of external building characteristics to derive instruction signals for comfort control operations of a building, and structure for directing the instructing signals to the building management control means for appropriate buildings. The external building characteristics include, in particular, the height of the building, the cross-sectional profile of the building, the exterior cross-sectional shape of the building, and the degree of shelter afforded by adjacent buildings.
As an additional example, U.S. Pat. No. 8,600,561 to Modi, et al., entitled “Radiant Heating Controls and Methods for an Environmental Control System”, describes devices, systems, and methods using predictive controls to condition an enclosure such as a home. Such controls may enhance the functionality of HVAC systems, especially when used with radiant heating systems. Modi, et al., describe thermostats that use model predictive controls and related methods.
As an additional example, U.S. Patent Application Publication No. 2010/0262298 by Johnson, et al., entitled “System and Method for Climate Control Set-Point Optimization Based on Individual Comfort”, describes a system and method for calibrating a set point for climate control including a sensor network having a plurality of sensors configured to report a climate condition. A database is configured to receive reports from the sensors and generate one or more profiles reflecting historic climate information and occupant preferences. A controller is configured to receive information from the profiles to generate a set point based upon an optimization program. The optimization program is implemented to balance competing goals in controlling climate control equipment.
As an additional example, U.S. Pat. No. 7,894,943 to Sloup, et al., entitled “Real-Time Global Optimization of Building Setpoints and Sequence of Operation”, describes a building heating/cooling system energy optimization method for a building having a heating/cooling system based on the steps of providing a mathematical model of the heating/cooling system, obtaining real-time weather information, reading the input water temperature, the output water temperature and the supply air temperature output to the building and transferring these values to an optimization system to calculate the efficiency profile of the heating/cooling system, then cooperatively optimizing and selecting those values to provide the highest efficiency profile.
As a further example, U.S. Patent Application Publication No. 2012/0259469 by Ward, et al., entitled “HVAC Control System and Method”, describes a method of controlling the HVAC system of a building. The system utilizes the thermal model of the building to continuously plan a daily HVAC operating schedule for the building. The thermal model uses a series of parameters fitted to historical thermal data for the building. The daily operating plan is an optimization of a combination of operator preferences that includes user comfort, power consumption and power costs. External inputs that can affect the operating plan include electricity pricing data, weather forecasts and occupant comfort satisfaction data. The human comfort model is augmented by means of data feedback by users of the building.
As a final example, U.S. Patent Application Publication No. 2014/0148953 by Nwankpa, et al., entitled “Dynamic Load Modeling of A Building's Energy Consumption for Demand Response Applications”, describes a dynamic electrical load model for a HVAC chiller for use in demand response applications. A dynamic model accurately models the electrical energy consumption of a HVAC chiller in response to changes in building temperature control, i.e., via thermostat. Raising or lowering the outlet chilled water temperature is the action used to increase or decrease the electric power, and for demand side response.
While addressing important areas of building energy use optimization by using techniques like building energy modeling, control set point optimization, and model predictive control, one problem with existing methods and systems for building HVAC control such as those described in the above examples, is that they do not provide the degree of granular thermal zone-level comfort control, while optimizing overall energy use, that is required for today's buildings and networks of buildings.
A need therefore exists for an improved method and system for predictive building control for optimizing energy use and thermal comfort for a building or network of buildings. Accordingly, a solution that addresses, at least in part, the above and other shortcomings is desired.